STAT331 Final Project - Linear Regression

Author

Thien An Tran, Tejasree Kandibanda, Matthew Huang, Chloe Anbarcioglu

Data Visualizations

Plot 1:

Code
murder_happiness_summary <- murder_happiness |>
  group_by(country, year) |>
  summarise(avg_murder_rate = mean(murder_rate_per_100k),
            avg_happiness_score = mean(happiness_score)) |>
  ungroup()

animated_plot <- ggplot(murder_happiness_summary,
                        aes(x = avg_murder_rate,
                            y = avg_happiness_score,
                            color = as.factor(year))
                        ) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, color = "black") +
  labs(title = "Relationship Between Murder Rate and Happiness Score (2005-2019)",
       subtitle = "Average Happiness Score",
       x = "Average Murder Rate per 100k People",
       y = "",
       color = "Year") +
  transition_time(year) +
  enter_fade() +
  exit_fade()

animate(animated_plot, renderer = gifski_renderer())

Plot 2:

Code
murder_happiness |>
  group_by(country) |>
  summarise(avg_murder_rate = mean(murder_rate_per_100k),
            avg_happiness_score = mean(happiness_score)) |>
  ggplot(aes(x = avg_murder_rate, 
             y = avg_happiness_score)
         ) +
    geom_point(color = "steelblue") +
    geom_smooth(method = "lm", se = FALSE, color = "black") +
    labs(title = "Relationship Between Murder Rate and Happiness Score",
         x = "Average Murder Rate (per 100k)", y = "Average Happiness Score") +
    theme_minimal()